Characterization of flavor substances in cooking and seasoned cooking brown seaweeds by GC-IMS and E-nose

Graphical abstract


Introduction
Algae is a kind of heterogeneous plant group with a long history without root and leaf system, which is mainly divided into microalgae and macroalgae (seaweeds) (Gupta & Abu-Ghannam, 2011).The bioactive substances found in seaweeds include lipids, proteins, polysaccharides, phenols, and pigments.They have biological activities that include those that are antibacterial, anti-cancer, anti-inflammatory, anti-diabetes, and anti-obesity (Sapatinha et al., 2022).In addition, seaweeds' secondary metabolites are a good source of numerous vitamins and minerals that the body need, such as vitamin A, C, D and E, niacin and folic acid, calcium, sodium, potassium, etc. (Pereira, 2005).As a result, seaweeds have long been a healthy food source and part of the diet of Asians (Wijesinghe & Jeon, 2012).They are also attracting attention as a valuable source of functional ingredients in the nutritional, medical and cosmetic industries (Park & Lee, 2021).Based on their chemical makeup, seaweeds are divided into green, brown, and red seaweed, with brown seaweed being the most popular for human consumption (Jiang et al., 2021).
Undaria pinnatifida (U. pinnatifida) and Laminaria japonica (L.japonica) are the most commonly consumed edible brown seaweed.For dietary or medical purposes, they are seen as a potential sustainable marine resource.They have potential health advantages since they are rich source of bioactive substances, including dietary fiber, polyphenols, fatty acids and carotenoids (Yue et al., 2022).For example, U. pinnatifida is widely regarded as a long-standing "longevity food" or "sea of vegetables" in many Western countries (Martinez-Villaluenga et al., 2018).The classic ancient Chinese text, Materia Medica, documented its diuretic and laxative properties.It has been used throughout Chinese history to treat conditions such as hyperthyroidism, oedema and haemorrhoids (Zeng et al., 2022).Previous studies have revealed that L. japonica has beneficial health effects such as antioxidant, immunomodulatory and hypolipidemic activities (Guo et al., 2014, Huang, Wen, Gao, & Liu, 2010, Zha et al., 2015).In addition to containing a wide range of biologically active substances, U. pinnatifida and L. japonica have a special marine aroma.Li et al. (2023) found that some volatile compounds in seaweed have a significant impact on its flavor.These volatile compounds produce different odors, such as "seafood", "licorice", "spices", "honey", and "fruit", which can affect consumer preference for seaweed food.Although a few studies have reported the volatile component composition of seaweeds, the flavor composition of seaweeds treated with different cooking techniques and seasoning liquids remains unclear (Lu, Yosemoto, Takayama, Satomi, & Akakabe, 2018).
The role of seasoning in the food industry, catering industry and

Table 1
The volatile compounds identified by GC-IMS in U. pinnatifida, seasoning U. pinnatifida, L. japonica and seasoning L. japonica under different cooking techniques.domestic cooking is becoming more and more important.It is common for people to add seasonings to vegetables when cooking and processing them to make them more palatable.Studies have shown that improving the palatability and flavor of vegetables or vegetable dishes increases the acceptance of vegetables (Manero et al., 2017).Seasonings can mask or eliminate some of the undesirable flavors, enhance the color of food, and improve the taste and texture or appearance of vegetables, thus directly affecting people's enjoyment of the dish and increasing their appetite.In addition, some seasonings have their own nutritional elements, which are beneficial to human health when used in moderation.Therefore, seasoning plays an important part in the cooking of vegetables.For example, a study of children by Fisher et al. (2012).found that seasoning sauces affect vegetable intake.Manero's study found that seasoned broccoli and string beans were more popular with consumers than the unseasoned versions (Manero et al., 2017).
Volatile flavor compounds have a significant role in the flavor of food.They play a crucial role in the assessment of food products, as they are a key determinant of consumer interest and acceptance (C.Li, Al-Dalali, Wang, Xu, & Zhou, 2022).Different cooking methods improved the organoleptic and textural characteristics of brown seaweeds.For example, microwave-treated Undaria pinnatifida retained color, polysaccharides and total phenolic content better (Jiang et al., 2021).Cooking methods directly affect the nutritional properties and final composition of the food, while volatile flavor substances released during cooking have a significant effect on the taste and aroma of brown seaweeds.Different seasonings and cooking techniques will result in a variety of food flavors that may change greatly from raw ingredients.In recent years, instrumental analytical techniques have been developed to identify volatile flavor components in food.This enables a better understanding of the relationship between the chemical composition of food flavors and human senses when combined with subjective sensory assessments.It provides a more comprehensive and objective basis for people to evaluate food flavors (Wang, Chen, & Sun, 2020).Gas chromatography-ion mobility spectrometry (GC-IMS) is a very common instrumental analytical technique for the determination of volatile flavor compounds in foods.It is a new gas phase separation technique combining ion mobility spectrometry with gas chromatography.It has a fast detection time, no pre-treatment and stable detection results.Simultaneously, it overcomes the disadvantages of poor resolution of ion mobility spectrometry, and has been widely used in the analysis of flavor substances in food (Liu et al., 2021).For example, Guo et al. (2021) used CG-IMS to identify the aroma characteristics of fresh tea leaves and oolong tea.For the analysis of food flavors, electronic nose (E-nose) is also frequently used.The E-nose is a technology used for detecting aromas, using an array of gas sensors and pattern recognition technology for olfactory recognition.It has the advantages of low cost and high degree of automation, providing the overall information of volatile compounds and flavor for the detected samples.However, it cannot provide a detailed analysis of the sample (Yang et al., 2022).The GC-IMS and E-nose technologies may create a fingerprint and radar spectrum of volatile organic chemicals, allowing for direct sample comparison.The combination of the two technologies provides a reliable technical basis for the comprehensive analysis of food flavors.
In this study, we used the sensitivity and rapidity of GC-IMS detection combined with E-nose to analyze the effects of seasoning solution and different cooking techniques on the flavor compounds in U. pinnatifida and L. japonica, and to establish the corresponding flavor fingerprints and E-nose radar maps.This study aimed to fill the current research gap by detecting and analyzing flavor compounds in brown seaweeds (U. pinnatifida and L. japonica) treated with seasoning and different cooking methods through GC-IMS coupled with E-nose.And there were few relevant reports.Therefore, it provides a reference for the subsequent processing of edible brown seaweeds for aroma characterization and quality control, and provides a basis for the study of the flavor characteristics of edible brown seaweeds.

Pretreatment of U. pinnatifida and L. japonica
In order to remove the salt on the surface of salted U. pinnatifida, it was washed three to four times with deionized water.Then immersed it in water until it reached the expanded state.After removing the excess water, cut the U. pinnatifida into 6 cm long and 0.5 cm wide samples.
L. japonica was soaked in water for 30 min and then taken out.The excess water on the surface was removed and cut into 5 cm long and 2 cm wide slices.
One part of the pre-treated U. pinnatifida and L. japonica samples was used for subsequent cooking and the other part was used to prepare seasoning samples for cooking afterwards.

Preparation of seasoning samples
The seasoning solution of L. japonica and U. pinnatifida was prepared as follows: 8 g white granulated sugar, 5 g white vinegar, 10 g mature vinegar, 5 g soy sauce, 1.5 g monosodium glutamate, 1.8 g edible salt (0.5 g edible salt for U. pinnatifida sample) dissolved in 100 mL of water to obtain the seasoning solution.
The pre-treated shredded U. pinnatifida and L. japonica slices were soaked in the seasoning solution at 5 ℃, L. japonica slices were soaked for 15 min, and the shredded U. pinnatifida for 2 min.Each sample was 50 g.L. japonica slices and shredded U. pinnatifida samples were immersed in 0.5 % calcium chloride for 2 min and 1.5 min respectively for subsequent cooking.

Cooking conditions
The pre-treated samples and the prepared seasoning samples were cooked separately in different techniques, each at 50 g.

High pressure (HP) cooking
50 g of unseasoned pretreatment samples and 50 g of seasoned samples were taken and placed in the glass case (830 mL, Anhui Deli Daily Glass Co., Ltd., Anhui, China) in an electric pressure cooker (YBD50-90A1(B), Zhangzhou Wanlida Appliance Co., Ltd., Zhangzhou, China), the U. pinnatifida and L. japonica samples were cooked for 15 min and 20 min respectively.

Microwaving
Shredded U. pinnatifida and L. japonica slices samples were mixed with 130 mL and 150 mL of deionized water respectively, placed in a heat-resistant glass box (KH-8676, Xitianlong Technology Development Co., Ltd., Tianjin, China) and cooked in a microwave oven (NE-1753, Panasonic Co., Ltd., Kadoma, Japan) at 1700 W for 3 min and 4 min.

Air frying (AF)
The samples were placed in the foil wrap (ZY2242, Suzhou Spike Aluminum Foil Co., Ltd, Suzhou, China), which was folded to a size of 20 cm × 20 cm to cover the samples, and then placed in an air fryer (HD 9651, Philips (China) Investment Co. Ltd., Shenzhen, China) at 180 • C. The shredded U. pinnatifida and L. japonica slices samples were cooked for 15 min and 18 min respectively.

Steaming
The U. pinnatifida and L. japonica samples were mixed with deionized water in a 1:1 ratio and crushed in a wall breaker (JYL-C010, Joyoung Co., Ltd, Jinan, China) for 45 s.Then, they were steamed in a steamer (QVL1526-1, Zhejiang Aishida Electric Co., Ltd., Taizhou, China) for 10 min and 15 min respectively.

Baking
The samples were baked at 170 • C in the oven (SCC WE 101/01, Landsberg a. Lech, Germany), choosing a four-stage wind force, and the U. pinnatifida and L. japonica samples were baked for 8 min and 10 min respectively.
The cooked samples were quickly cooled down with ice water, evacuated into foil vacuum bags and stored at − 20 • C until analysis.

Gas chromatography-ion mobility spectrometry (GC-IMS) analysis
Volatiles compounds in U. pinnatifida and L. japonica samples were analyzed by GC-IMS with modifications as described in the method of Zhang et al. (2022).Analysis was carried out using GC in combination with IMS instrumentation (Flavourspec®-G.A.S. Dortmund Company, Dortmund, Germany).5 g of chopped sample was weighed into a 20 mL headspace flask and incubated at 60 ℃ for 15 min at 500 rpm before being measured.The injection volume was set to 500 μL and the injection needle temperature was 85 ℃.The volatile compounds were separated on an MXT-WAX column (30 m × 0.53 mm × 1 µm, RESTEK, PA, USA) at a column temperature of 60 ℃.Nitrogen was used as the detection carrier gas and the drift tube temperature was 45 ℃.The initial flow rate was 2 mL/min, which was held for two minutes and then linearly increased to 10 mL/min over 10 min and finally to 100 mL/min over the remaining 20 min.Three replicates on average were used for the final analysis.

Determination of E-nose
Electronic nose (PEN3, AIRSENSE, Schwerin, Germany) was used to detect odors.The test conditions were modified according to the method of Ma, Mu, and Zhou (2021).1.0 g of sample was accurately weighed in a 10 mL vial and each sample was measured 3 times in parallel.Measurement conditions: 60 s for sensor cleaning, 10 s for auto-zeroing, 5 s for sample preparation, and 60 s for data detection.

Statistical analysis
Data was examined using IBM SPSS Statistics 26 (IBM Corporation, Armonk, NY, USA).On the FlavourSpec® flavor analyzer, the accompanying software was used to view the analytical spectra and qualitative and quantitative data, and the database was called for qualitative analysis of the substances.The Reporter plug-in compares the spectral differences between samples, the GalleryPlot plug-in creates fingerprint profiles and compares the volatile organic compounds differences between samples, and the Dynamic PCA plug-in performs dynamic PCA.In PCA analysis, principal component analysis was created using signal intensity to highlight the differences in volatile components.Statistical comparisons were conducted using analysis of variance (ANOVA) and Duncan's multiple range test.Significant differences were determined using SPSS software with a level of p < 0.05.

Results and discussion
The results of the identification of volatile compounds in the samples were shown in Table 1.72 compounds were identified in U. pinnatifida and seasoning U. pinnatifida.L. japonica and seasoning L. japonica contained 70 compounds.Certain substances can generate several signals or spots depending on their concentration (e.g., due to the presence of monomers, dimers, or trimers) (Li et al., 2019).

U. pinnatifida
GC-IMS was used to analyze the differences in volatile compounds in U. pinnatifida after different cooking methods.The results for U. pinnatifida treated with different cooking techniques were shown in the 3D topography in Fig. 1A.The drift time was displayed on the X-axis, the retention time on the Y-axis, and the ion peak intensity on the Z-axis.The fractions were tentatively identified by comparing their retention indices (RI) and mass spectrums with those of internal databases and reference compounds (Guo, Ho, et al., 2021).Each dot in the spectrum represented a volatile compound, with red representing high concentrations and white representing low concentrations.The ion peaks can distinguish between monomers, dimers and multimers of the same substance, depending on the content and nature of the substance.The differences in volatile flavor compounds in U. pinnatifida from the different cooking methods can be visualized in the Fig. 1A.However, in order to compare the discrepancies, the top view was obtained below due to the difficulty of observation.The difference comparison pattern for the top view of the GC-IMS 3D topography was displayed in Fig. 1B along with the normalized ion migration times and positions of the reaction ion peaks (RIP).The raw sample spectra were selected as a reference and the spectra of the reference were deducted from the other samples.The background would have been white if the volatile taste compounds in both samples were identical, with red denoting a substance's concentration being higher than the reference and blue denoting its concentration being lower.The significant increase in the number of red dots in the baked U. pinnatifida samples could be attributed to the increased production of volatile flavor substances due to the promotion of the Maillard reaction during the baking process (Suri, Singh, Kaur, Yadav, & Singh, 2020).
A topographic map can clearly display the cyclical changes in volatile elements.However, making an accurate assessment of the closely related compounds on the map is challenging (Yang et al., 2019).The Gallery Plot plug-in was used to automate the generation of fingerprints of all peaks to be evaluated for various cooking samples in order to better understand the variations of volatile matter in different cooking samples (Fig. 1C).Each column showed the peaks of the same volatile chemical in U.pinnatifida treated with various cooking techniques, and the peaks chosen from each sample were represented by a row.Individual dots indicated a volatile compound, and the shading of the color denoted the level of that volatile compound, with brighter color indicating higher levels.By comparing the dynamics of volatile compounds between samples through fingerprinting, changes in volatile compounds (increase, decrease, disappearance or fluctuation) between different cooking methods can be determined (Xuan et al., 2022).M, D and T in brackets after the substance name represented the monomer, dimer and trimer of the substance, respectively.Fig. 1C showed the differences in volatile organic chemicals between samples as well as the full information on volatile organic compounds for each sample.The substances in the red box were highest in raw U. pinnatifida sample and included 1hydroxypropan-2-one, propionic acid, 3-methyl-1-butanol, 3-octanone, 2-Methyl-1-propanol, 1-octen-3-ol and ethanol, indicating that these cooking methods may have caused a loss of these flavor compounds.The substances in the yellow box were the most abundant in the baked samples and included 3-methyl-2-pentanone, (Z)-hept-4-enal, methyl acetate, heptan-2-one, butan-1-ol, isopropyl acetate, 1-octen-3-one, butanal, 2-pentylfuran, heptanal, acrolein, 2-methyl-2-pentenal, dimethyl sulfide, 3-methyl-2-butenal, (Z)-hex-3-enol, butan-2-one, (E)-2-hexenal, 1-pentanol, (E)-2-pentenal, 1-propanol, hexanal, cis-2penten-1-ol, 2-ethylfuran, trans-2-octenal, 1-penten-3-one, 6-methylhept-5-en-2-one and 1-penten-3-ol.Baking may have provided gentler and more sustained heating, which helped more kinds of compounds to react thermally, leading to richer flavors.The substances in the orange box were highest in one type of U. pinnatifida, with nonanal and octanal being the most abundant in the AF cooking.They were aliphatic aldehydes, which usually with aromas of citrus, orange, fat, or greasy.Air frying was cooking by strong convection air flow.The air movement may result in more oxygen being involved in chemical reactions in the ingredients, including oxidation, which promoted the production of nonanal and octanal.Cyclopentanone, ethyl acetate, pentanal, ethyl acetate and benzaldehyde were present in the highest amounts in the steamed samples.Steaming was usually done at relatively high but mild temperatures.This may prompt some chemical reactions that make it easier for some volatile compounds such as cyclopentanone and ethyl acetate to evaporate from the ingredients.The compounds in the green box were the least abundant in one variety of U. pinnatifida, with (E)-2heptenal, propionaldehyde and propan-2-one being the least abundant in raw sample, acetic acid was the least abundant in baking.
Fig. 1D showed the principal component analysis (PCA) of U. pinnatifida in different cooking methods.And all the data included in PCA came from the same batch of tests.PCA is a multivariable statistic method for assessing correlations between various variables.It is a multidimensional data analyzer tool for analyzing multidimensional data sets with quantifiable variables (An, Liu, Hao, Wang, & Tang, 2020).The original variables, which contain 3D data concerning retention time, drift time, and ion signal intensity, are used to create a number of principal components (as variables, mainly as observations) (Wang et al., 2019).Signal intensities are used to emphasize changes in volatile components, which may be seen between samples, in order to synthesize the issue.Additionally, the graph can visualize the differences between the samples, samples with overlap or closeness have scent profiles that are comparable.On the other hand, differences become more obvious the further apart the samples are (Hernandez et al., 2016, Song et al., 2020).In general, the PCA model was regarded as the preferred separation model when the total contribution of PC1 and PC2 reached 60 % (Wu et al., 2015).As seen in Fig. 1D, the contribution of PC1 was 49 % and PC2 was 25 %.The accumulated contribution was 74 %, which was adequate to interpret how comparable the various samples were.Fig. 1D revealed that the difference between samples from the baking group and the other samples was significant.
The PCA results made it quite evident that that the seasoned U. pinnatifida samples treated with different cooking techniques could be distinguished in the distribution map in a relatively independent space.In Fig. 2D, the distribution of the HP, microwaving and AF treated seasoned samples was close to each other, indicating little change in flavor substances in the samples, while there was a significant deviation in the baking samples, indicating a significant difference in volatile flavor compounds in the baking samples.

Differences in aroma distribution between samples analyzed using Enose
To comprehend aroma properties and volatile chemicals, the combined analysis of GC-IMS and E-nose data was essential (X.H. Huang et al., 2019, Lan et al., 2021, Niu et al., 2019).The E-nose simulated the human olfactory system and was widely used to identify odors (Baietto & Wilson, 2015, Xu et al., 2020).In order to accurately assess the aroma spectrum of U. pinnatifida and L. japonica, we used the E-nose, which was frequently used for aroma identification and discrimination and which provided an overall spectrum of volatile compounds but not specific information on the composition and amount of volatile compounds (Wu et al., 2021).As shown in Fig. 5A for the E-nose radar map of U. pinnatifida and seasoning U. pinnatifida under different cooking techniques, there were differences in sensor response values between the samples, indicating different aroma distributions between them.The response values of U. pinnatifida treated with different cooking techniques basically overlapped, which indicated that the cooking techniques had no significant effect on the aroma distribution in the U. pinnatifida.The response values of W1W (mainly sensitive to terpenoids and organic sulfides), W2W (mainly sensitive to aromatic compounds and organic sulfides) increased significantly in the seasoning U. pinnatifida, while the other response values increased slightly (Junxing et al., 2022).Among them, the response values of baked seasoning U. pinnatifida were significantly higher than the other groups, which was consistent with the results of GC-IMS (Fig. 2B), indicating baking produced richer flavor substances.The L. japonica samples were also the same as the U. pinnatifida samples before seasoning, with a dense distribution among the cooking groups and no significant changes as in Fig. 5B.Similarly, the response values of W1W and W2W were significantly increased in the E-nose for the seasoning L. japonica samples.These results may be related to the substances in the added seasoning.

Conclusion
The combination of GC-IMS and electronic nose was an effective analytical method for volatile spectra and flavors.In this study, GC-IMS was used to determine and characterize volatile compounds in seasoning solution treatment and different cooking techniques.72 characteristic volatile compounds were detected in U. pinnatifida before and after seasoning.And a total of 70 compounds were detected in seasoned and unseasoned L. japonica.Although the GC-IMS results showed that the flavor compounds of the baked samples differed significantly from the other cooking techniques, the E-nose analysis showed that overall the treatments of the different cooking techniques had little effect on the flavor compounds in U. pinnatifida and L. japonica.In contrast, the seasoned edible brown seaweeds samples had a better flavor profile relative to the unseasoned samples.The different volatile flavor components of brown seaweeds processed by seasoning solution and different cooking methods not only provide a reference for the commercial processing of brown seaweeds, but also provide a reference for different consumers to choose suitable cooking methods, so that they can find a cooking method that better meets their own tastes and needs.However, this study has some limitations.The effects of different cooking conditions (e.g.cooking time or temperature) and seasoning solution types need to be explored more in the future.

Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

. japonica and seasoning L. japonica
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Table 1
(continued ) MW: Molecular weight, RI: the retention index, Rt: the retention time, Dt: the drift time.